Legionella pneumophila, the causative agent of Legionnaires' disease, is a water born pathogenic bacteria commonly found in natural and manmade water systems such as rivers, lakes, wet soil, hot and cold water storage systems (being able to survive at temperatures between 6-63 °C, and proliferating between 20-45 °C), showerheads, cooling towers and spa pools. The main pathway of exposure to Legionella is by inhaling the aerosols containing the microorganism. Legionnaires' disease can be fatal if not diagnosed and treated at the right time. Practical Legionella control starts with a risk assessment of the water system and followed by the regular monitoring and water sampling. UK Health and Safety Executive (HSE) have implemented strict legislations to protect the public from Legionnaires' disease. This research highlights and addresses three major data gaps identified in Legionella control and management strategy employed in the UK and worldwide; namely, (i) the underestimation of microbiological threat in current cold water storage sampling strategy, (ii) the inability of current qPCR diagnostic methods to detect live Legionella in water samples, and (iii) the lack of predictive 'risk management system' for Legionella control in domestic water systems. During my PhD, 15 relevant cold water storage tanks (selected from more than 6000 tanks surveyed at different sites located in different London Boroughs) were used to investigate the risk factors that contribute towards Legionella proliferation, and revealed serious shortcomings in the appropriateness of the water sample taken for regulatory testing. Secondly, molecular biology research was carried out to develop an accurate, reliable and rapid testing method for the detection and quantification of live Legionella using qPCR techniques. This was successfully achieved by extracting RNA from a Legionella lenticule, converting the RNA into cDNA and amplifying the cDNA using qPCR techniques. Finally, regular monitoring data from 120 London buildings (60 known to be Legionella positive and 60 known to be Legionella negative) was used to identify the possible risk factors contributing towards Legionella outbreaks. Data for these factors was then used to develop a predictive risk model for Legionella contamination using Principal Component Analysis (PCA). The model was validated with 66 new London buildings and 9 out of London buildings. The model showed 100% accuracy in predicting the risk of Legionella by distinguishing infected and non-infected sites in London as well as for the sites in out of London.

O desafio de encontrar corretamente genes eucarioticos codificadores de proteinas nas sequencias genomicas e um problema em aberto. Neste trabalho, implementamos uma plata- forma, com o objetivo de melhorar a forma com que preditores de genes sao implementados e avaliados. Tres novas ferramentas foram implementadas: ToPS (Toolkit of Probabilistic Models of Sequences) foi o primeiro arcabouco orientado a objetos que fornece ferramentas para implementacao, manipulacao, e combinacao de modelos probabilisticos para representar sequencias de simbolos; MYOP (Make Your Own Predictor) e um sistema que tem como objetivo facilitar a construcao de preditores de genes; e SGEval utiliza grafos de splicing para comparar diferente anotacoes com eventos de splicing alternativos. Utilizamos nossas ferramentas para o desenvolvimentos de preditores de genes em onze genomas distintos: A. thaliana, C. elegans, Z. mays, P. falciparum, D. melanogaster, D. rerio, M. musculus, R. norvegicus, O. sativa, G. max e H. sapiens. Com esse desenvolvimento, estabelecemos um protocolo para implementacao de novos preditores. Alem disso, utilizando a nossa plata- forma, desenvolvemos um fluxo de trabalho para predicao de genes no projeto do genoma da cana de acucar, que ja foi utilizado em 109 sequencias de BAC geradas pelo BIOEN (FAPESP Bioenergy Program). / The challenge of correctly identify eukaryotic protein-coding genes in the genomic se- quences is an open problem. In this work, we implemented a plataform with the aim of improving the way that gene predictors are implemented and evaluated. ToPS (Toolkit of Probabilistic Models of Sequence) was the first object-oriented framework that provides tools for implementation, manipulation, and combination of probabilistic models that represent sequences of symbols. MYOP (Make Your Own Predictor) facilitates the construction of gene predictors. SGEval (Splicing Graph Evaluation) uses splicing graphs to compare dif- ferent annotations with alternative splicing events. We used our plataform to develop gene finders in eleven distinct genomes: A. thaliana, C. elegans, Z. mays, P. falciparum, D. me- lanogaster, D. rerio, M. musculus, R. norvegicus, O. sativa, G. max e H. sapiens. With this development, we established a protocol for implementing new gene predictors. In addi- tion, using our platform, we developed a pipeline to find genes in the 109 sugarcane BAC sequences produced by BIOEN (FAPESP Bioenergy Program).

Submitted by Joana Azevedo (joanad@id.uff.br) on 2017-08-15T18:24:14Z No. of bitstreams: 1 Dissert Wilson Vanderlei Costa Sousa.pdf: 2498072 bytes, checksum: 2cbeac670037f8e2920f8b2932194e62 (MD5) / Approved for entry into archive by Biblioteca da Escola de Engenharia (bee@ndc.uff.br) on 2017-09-04T16:45:28Z (GMT) No. of bitstreams: 1 Dissert Wilson Vanderlei Costa Sousa.pdf: 2498072 bytes, checksum: 2cbeac670037f8e2920f8b2932194e62 (MD5) / Made available in DSpace on 2017-09-04T16:45:28Z (GMT). No. of bitstreams: 1 Dissert Wilson Vanderlei Costa Sousa.pdf: 2498072 bytes, checksum: 2cbeac670037f8e2920f8b2932194e62 (MD5) Previous issue date: 2015-03-26 / Partindo do princípio de que os custos ocultos podem estar presentes em todas as entidades, inclusive nas instituições públicas brasileiras – onde as disfunções resultantes da interação de estruturas atrofiadas com comportamentos atrofiados fazem com que estes custos se perpetuem – esta pesquisa busca responder, dentro do contexto da administração pública, como a Gestão do Capital Intelectual pode contribuir para melhor administrar os custos ocultos. Neste sentido, deve-se levar em consideração que as técnicas contabilísticas não podem reconhecer esse tipo de custo e que a Nova Gestão Pública tem buscado técnicas de gerenciamento aplicáveis ao setor público que resultem no aumento da eficiência, transparência e qualidade dos serviços prestados ao cidadão. Para tanto, primeiramente buscou-se na literatura os principais conceitos, origens, natureza e classificação dos custos ocultos e do Capital Intelectual, bem como os modelos e técnicas para sua identificação e mensuração. A partir daí, realizou-se um estudo de caso no Departamento de Contabilidade e Finanças da Universidade Federal Fluminense e áreas correlacionadas. Foi aplicado um questionário baseado em método de reconhecimento e mensuração do Capital Intelectual do setor público, o qual pode apresentar resultados que direcionam para insuficiência, estagnação ou excelência, sendo os dois primeiros grandes indicadores da ocorrência de custos ocultos. Foi possível verificar que a Gestão do Capital Intelectual no Serviço Público pode ser aplicada de forma a contribuir na regulação dos comportamentos e estruturas atrofiadas, objetivando com isso diminuir as disfunções que geram custos ocultos e produzem efeitos destrutivos para a performance eficiente do serviço público. / Assuming that hidden costs may be present in all entities, including Brazilian public institutions – where dysfunctions resulted from the interaction between both atrophied structures and atrophied behaviors make these costs to perpetuate themselves – this research aims to answer, within public administration context, how intellectual capital management can help to improve hidden costs management as well. In this sense, it must be taken that accounting techniques cannot recognize this kind of cost and the New Public Management has searched for management techniques applicable to public sector that result in increasing efficiency, transparency and quality of services provided to citizens. To do so, first one has sought in literature about the main concepts, origins, nature and classification of hidden costs and Intellectual Capital, as well as models and techniques for its identification and measurement. Thereafter, one has performed a case study in the Accounting and Finances Department of Federal Fluminense University and its related areas.It has been applied a survey based on a method for recognition and measurement of intellectual capital in public sector, which can produce results that lead to failure, stagnation or excellence, the first two ones are considered main indicators of the occurrence of hidden costs. Was possible to verify that the Intellectual Capital Management in Public Service can be applied in order to contribute for the regulation of behavior and atrophied structures, aiming this way to reduce dysfunctions that generate hidden costs and produce destructive effects for the efficient performance of the public service.

From 23 European and North American strains Euastrum humerosum/didelta species complex (Desmidiales) I have obtained 3 lineages in molecular marker trnGucc group II intron. I did not acquire significant and homogenous results in SSU intron. It is probable that the lineages of trnGucc intron are very young. SEM revealed one central pore in cell wall and five bulges. The lineages were significantly different in their shape and dimensions. The lineages differentiated mainly in their length and breadth of the cells. The lineages inside morphotype E. humerosum differentiated in shape and dimensions of the polar lobe. The lineages inside morphotype E.didelta differentiated in shape and dimensions of the neck. That was ascertained using the geometric morphometrics with the measuring. Linear discriminant analysis of the desmids from literature revealed that is possible to partly discriminate groups of the varieties (E. humerosum var. parallelum and E. didelta in lineage A; two formae E. didelta f. val Piora and E. didelta f. latior in lineage B; E. didelta var. inermiforme and E. humerosum var. affine in lineage C). Key words: desmids, species, hidden diversity, molecular phylogenetics, geometric morphometrics, Euastrum, scanning electron microscopy

HMMs de perfil são um método poderoso para modelar a diversidade de sequências biológicas e constituem uma abordagem muito sensível para a detecção de ortólogos remotos. Uma potencial aplicação de tais modelos é a detecção de vírus emergentes e novos elementos genéticos móveis. Nosso grupo desenvolveu recentemente o GenSeed-HMM, um programa que emprega HMMs de perfil como sementes para montagem progressiva de genes-alvo, utilizando tanto dados genômicos como metagenômicos. No presente trabalho foi desenvolvido o TABAJARA, um programa para o desenho racional de HMMs de perfil. Partindo de um alinhamento de múltiplas sequências, o TABAJARA é capaz de encontrar blocos que são (1) conservados ou (2) discriminativos para dois ou mais grupos de sequências. O programa utiliza diferentes métricas para atribuir pontuações posição-específicas ao longo de todo o alinhamento e utiliza então uma janela deslizante para encontrar as regiões com maiores pontuações. Blocos de alinhamento selecionados são então extraídos e utilizados para construir HMMs de perfil. Para validar o método, o programa TABAJARA foi empregado para a construção de modelos para vírus do gênero Flavivirus e para fagos da família Microviridae. Em ambos os grupos virais foi possível se obter modelos de ampla abrangência, capazes de detectar todos os membros de um respectivo grupo taxonômico, e modelos de abrangência mais restrita, específicos para espécies distintas de Flavivirus (ex. DENV, ZIKV ou YFV) ou subfamílias de Microviridae (ex. Alpavirinae, Gokushovirinae e Pichovirinae). Em outra validação, foram utilizadas sequências da endonuclease Cas1 para se obter modelos capazes de diferenciar CRISPRs de casposons, esses últimos representando uma superfamília de transposons de DNA autossintetizantes, os quais originaram o sistema de imunidade CRISPR-Cas de procariotos. O TABAJARA conseguiu gerar modelos específicos de Cas1 derivada de casposons, permitindo sua diferenciação em relação aos seus ortólogos de CRISPRs. No presente trabalho foi desenvolvido ainda o HMM-Prospector, uma ferramenta que utiliza um conjunto de HMMs de perfil para a triagem de dados de sequenciamento genômico ou metagenômico. O programa informa quais são os modelos mais reconhecidos pelas leituras, sob valores de corte de pontuação definidos pelo usuário, assim como quantas leituras são detectadas por cada modelo. Com esta informação, os modelos mais relevantes podem ser utilizados como sementes em montagens progressivas com o programa GenSeed-HMM, dentro de uma abordagem integrada para a construção de modelos e sua aplicação. Finamente, foi desenvolvido o e-Finder, um aplicativo genérico para a detecção e extração de elementos multigênicos a partir de genomas ou metagenomas montados utilizando HMMs de perfil. O e-Finder executa buscas de similaridade entre os HMMs de perfil e as sequências traduzidas dos dados montados e checa, em seguida, se os critérios de sintenia pré-definidos foram atendidos, incluindo o número mínimo de genes, a ordem dos genes e as distâncias intergênicas. As sequências dos elementos são então extraídas, as regiões codificantes (ORFs) identificadas e traduzidas conceitualmente em sequências completas de proteínas. Para validar esta ferramenta, foram empegados dois estudos de caso, profagos da família Microviridae e casposons, utilizando-se HMMs de perfil específicos, construídos com o programa TABAJARA. Em ambos os casos, o e-Finder foi executado usando-se a base de dados PATRIC, um repositório com mais de 135.000 genomas de bactérias e arqueias. Foram identificados um total de 91 contigs positivos para casposons a partir de 79 genomas distintos. No caso dos Microviridae, foram encontrados 104 profagos candidatos, estendendo o conhecimento da gama de hospedeiros bacterianos. Em ambos os casos, análises filogenéticas confirmaram a correta atribuição taxonômica das sequências positivas. Os programas desenvolvidos neste trabalho podem ser utilizados isoladamente ou em combinação para detectar e discriminar sequências conhecidas ou remotamente relacionadas. Juntamente com o GenSeed-HMM, estes programas constituem um conjunto integrado de ferramentas com potencial aplicação na busca de novos vírus e elementos genéticos móveis, bem como em qualquer outra tarefa relacionada à detecção e/ou discriminação de subgrupos de famílias de sequências nucleotídicas ou proteicas / Profile HMMs are a powerful way of modeling sequence diversity and constitute a very sensitive approach to detect remote orthologs. A potential application of such models is the detection of emerging viruses and novel mobile genetic elements. Our group has recently developed GenSeed-HMM, a tool that employs profile HMMs as seeds for gene-targeted progressive assembly using either genomic or metagenomic data. In this work we developed TABAJARA, a program for the rational design of profile HMMs. Starting from a multiple sequence alignment, TABAJARA is able to find blocks that are either (1) conserved across all sequences or (2) discriminative for two or more specific groups of sequences. The program uses different metrics to ascribe position-specific scores along the whole alignment and then uses a sliding-window to find top-scoring regions. Selected alignment blocks are then extracted and used to build profile HMMs. To validate the method, we employed TABAJARA to construct models for viruses of the Flavivirus genus and phages of the Microviridae family. In both viral groups we were able to obtain wide-range models, able to detect all members of the respective taxonomic group, and models that are specific to particular Flavivirus species (e.g. DENV, ZIKV or YFV) or Microviridae subfamilies (e.g. Alpavirinae, Gokushovirinae and Pichovirinae). In another validation, we used sequences of the endonuclease Cas1 to obtain models capable of differentiating CRISPRs from casposons, the latter elements representing a superfamily of self-synthesizing DNA transposons that originated the prokaryotic CRISPR-Cas immunity. TABAJARA succeeded to generate models specific to casposon-derived Cas1, enabling their differentiation from CRISPR orthologs. We also developed HMM-Prospector, a tool that can use a batch of profile HMMs to screen genomic or metagenomic sequencing data, reporting which profile HMMs are mostly recognized under user-defined score cutoff values, and how many reads are detected by each model. With this information, the most relevant models can be used as seeds in progressive assemblies with GenSeed-HMM program, providing an integrated approach for model construction and application. Finally, we developed e-Finder, a generic application for detecting and extracting multigene elements from assembled genomes or metagenomes using profile HMMs. e-Finder runs similarity searches of profile HMMs against translated sequences of the assembled data and then checks if pre-defined syntenic criteria have been fulfilled, including minimum number of genes, gene order and intergenic distances. Element sequences are then extracted, their ORFs identified and conceptually translated into full-length protein sequences. To validate the tool, we employed two distinct case studies, prophages of the Microviridae family and casposons, using specific profile HMMs constructed by TABAJARA. In both cases, we executed e-Finder using the PATRIC database, a repository with over 135,000 bacterial and archaeal genomes. We identified in total 91 casposon-positive contigs from 79 distinct genomes. In the case of Microviridae, we found a total of 104 provirus candidates, extending the known range of bacterial hosts. In both cases, phylogenetic analyses confirmed the correct taxonomic assignment of the positive sequences. The programs developed in this work can be used alone or in combination to detect and discriminate known or distantly related sequences. Together with GenSeed-HMM, these programs provide an integrated toolbox with potential application in the search of novel viruses and mobile genetic elements, as well as in any other task related to the detection and/or discrimination of subgroups of DNA or protein sequences.

The hidden state Markov (HSM) model is introduced as a new conceptual framework for modelling long-term persistence in hydrological time series. Unlike the stochastic models currently used, the conceptual basis of the HSM model can be related to the physical processes that influence long-term hydrological time series in the Australian climatic regime. A Bayesian approach was used for model calibration. This enabled rigourous evaluation of parameter uncertainty, which proved crucial for the interpretation of the results. Applying the single site HSM model to rainfall data from selected Australian capital cities provided some revealing insights. In eastern Australia, where there is a significant influence from the tropical Pacific weather systems, the results showed a weak wet and medium dry state persistence was likely to exist. In southern Australia the results were inconclusive. However, they suggested a weak wet and strong dry persistence structure may exist, possibly due to the infrequent incursion of tropical weather systems in southern Australia. This led to the postulate that the tropical weather systems are the primary cause of two-state long-term persistence. The single and multi-site HSM model results for the Warragamba catchment rainfall data supported this hypothesis. A strong two-state persistence structure was likely to exist in the rainfall regime of this important water supply catchment. In contrast, the single and multi-site results for the Williams River catchment rainfall data were inconsistent. This illustrates further work is required to understand the application of the HSM model. Comparisons with the lag-one autoregressive [AR(1)] model showed that it was not able to reproduce the same long-term persistence as the HSM model. However, with record lengths typical of real data the difference between the two approaches was not statistically significant. Nevertheless, it was concluded that the HSM model provides a conceptually richer framework than the AR(1) model. / PhD Doctorate

Derivative pricing, and in particular the pricing of options, is an important area of current research in financial mathematics. Experts debate on the best method of pricing and the most appropriate model of a price process to use. In this thesis, a ``Switching Black-Scholes'' model of a price process is proposed. This model is based on the standard geometric Brownian motion (or Black-Scholes) model of a price process. However, the drift and volatility parameters are permitted to vary between a finite number of possible values at known times, according to the state of a hidden Markov chain. This type of model has been found to replicate the Black-Scholes implied volatility smiles observed in the market, and produce option prices which are closer to market values than those obtained from the traditional Black-Scholes formula. As the Markov chain incorporates a second source of uncertainty into the Black-Scholes model, the Switching Black-Scholes market is incomplete, and no unique option pricing methodology exists. In this thesis, we apply the methods of mean-variance hedging, Esscher transforms and minimum entropy in order to price options on assets which evolve according to the Switching Black-Scholes model. C programs to compute these prices are given, and some particular numerical examples are examined. Finally, filtering techniques and reference probability methods are applied to find estimates of the model parameters and state of the hidden Markov chain. / Thesis (Ph.D.)--Applied Mathematics, 2003.

In this thesis two different problems in distributed sensor networks are considered. Part I involves optimal quantiser design for decentralised estimation of a two-state hidden Markov model with dual sensors. The notion of optimality for quantiser design is based on minimising the probability of error in estimating the hidden Markov state. Equations for the filter error are derived for the continuous (unquantised) sensor outputs (signals), which are used to benchmark the performance of the quantisers. Minimising the probability of filter error to obtain the quantiser breakpoints is a difficult problem therefore an alternative method is employed. The quantiser breakpoints are obtained by maximising the mutual information between the quantised signals and the hidden Markov state. This method is known to work well for the single sensor case. Cases with independent and correlated noise across the signals are considered. The method is then applied to Markov processes with Gaussian signal noise, and further investigated through simulation studies. Simulations involving both independent and correlated noise across the sensors are performed and a number of interesting new theoretical results are obtained, particularly in the case of correlated noise. In Part II, the focus shifts to the detection of faults in helicopter transmission systems. The aim of the investigation is to determine whether the acoustic signature can be used for fault detection and diagnosis. To investigate this, statistical change detection algorithms are applied to acoustic vibration data obtained from the main rotor gearbox of a Bell 206 helicopter, which is run at high load under test conditions.

<p>The aim with this study was to increase the knowledge about as well as shed light on hidden refugees’ living conditions by compiling research about hidden refugees’ living conditions and complete this research by doing a field survey with people with different knowledge and experience of hidden refugees’ living conditions. The result was analyzed on the basis of Nussbaum’s list of ten human abilities and the convention of human rights. The study showed that hidden refugees' living conditions are experienced as very critical, and characterized by lack of human rights as well as means to utilize and develop their abilities. The conclusion of the study is that hidden refugees’ living conditions could not be considered humane and that there is a need for ethics when treating hidden refugees.</p>

Le développement des véhicules autonomes a reçu une attention croissant ces dernières années, notamment les secteurs de la défense et de l'industrie automobile. L'intérêt pour l'industrie automobile est motivé par la conception de véhicules sûrs et confortables. Une raison commune derrière la plupart des accidents de la circulation est due au manque de vigilance du conducteur sur la route. Cette thèse se trouve dans le problématique de l'estimation des risques de collision pour un véhicule dans les secondes qui suivent en condition de circulation urbaines. Les systèmes actuellement disponibles dans le commerce sont pour la plupart conçus pour prévenir les collisions avant, arrières, ou latérales. Ces systèmes sont généralement équipés d'un capteur de type radar, à l'arrière, à l'avant ou sur les côtés pour mesurer la vitesse et la distance aux obstacles. Les algorithmes pour déterminer le risque de collision sont fondés sur des variantes du TTC (time-to-collision en anglais). Cependant, un véhicule peut se trouver dans des situations où les routes ne sont pas droites et l'hypothèse que le mouvement est linéaire ne tient pas pour le calcul du TTC. Dans ces situations, le risque est souvent sous-estimé. De plus, les instances où les routes ne sont pas tout droit se trouve assez souvent dans les environnement urbain ; par exemple, les rond point ou les intersections. Un argument de cette thèse est que, savoir simplement qu'il y ait un objet à une certaine position et à une instance spécifique dans le temps ne suffit pas à évaluer sa sécurité dans le futur. Un système capable de comprendre les comportements de déplacement du véhicule est indispensable. En plus, les contraintes environnementales doivent être prises en considération. Le cas le plus simple du mouvement « libre » est d'abord traité. Dans cette situation il n'ya pas de contraintes environnementales ou de comportement explicite. Ensuite, les contraintes environnementales des routes sur trafic urbain et le comportement des conducteurs des véhicules sont introduits et pris en compte explicitement. Cette thèse propose un modèle probabiliste pour les trajectoires des véhicules fondé sur le processus gaussien (GP). Son avantage est le pouvoir d'exprimer le mouvement dans le futur indépendamment de la discrétisation d'espace et d'état. Les comportements des conducteurs sont modélisés avec une variante du modèle de Markov caché. La combinaison de ces deux modèles donne un modèle probabiliste de l'évolution complète du véhicule dans le temps. En plus, une méthode générale pour l'évaluation probabiliste des risques de collision est présentée, où différentes valeurs de risque, chacun avec sa propre sémantique.